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The other uses elastic-net regression on historical supervisory data to estimate risk-weighted assets for small banks under simplified reporting. Its estimates feed into FINMA's risk assessment of small banks. In a report dated 14 October 2025 and published on 7 January 2026, the SFAO found that such AI methods can support and relieve specific supervisory tasks. It found that the systems already help in practice, for example in preparing data and analyses. It also found that FINMA has no structured procedure to measure the effect or cost-effectiveness of its AI systems. Project leads rated seven of 12 production systems as having little influence on supervision and four as not relevant.","category":"program","unexpected":false,"purpose":"FINMA's Data Innovation Lab built the two systems to support supervisors. 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Section 3.2, pp. 15-16.","title":"Prüfung des Einsatzes Künstlicher Intelligenz in der Aufsichtstätigkeit – Eidgenössische Finanzmarktaufsicht (EFK-25551)","url":"https://www.efk.admin.ch/wp-content/uploads/publikationen/berichte/wirtschaft_und_verwaltung/informatikprojekte/25551/d/25551_endgueltige_fassung_v04.pdf","date":"2026-01-07","written_by":"independent","quote":"Die Analysen der beiden ausgewählten KI-Systeme zeigen, dass KI-basierte Verfahren geeignet sind, um spezifische Fachfunktionen in unterschiedlichen Anwendungsbereichen der Aufsicht punktuell zu unterstützen und entlasten."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].upstream_sources":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"strategic_assessments[]":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"strategic assessments"},"summary":{"state":"value_present","value":{"kind":"record_fields","fields":{"summary":"The Swiss Federal Audit Office examined two FINMA systems, for press coverage and for risk estimates of small banks. It found that such AI methods support and relieve specific supervisory tasks.","account":"The Swiss Financial Market Supervisory Authority (FINMA) set up its Data Innovation Lab in 2018. By April 2025 the lab had ten AI systems in production. The Swiss Federal Audit Office (SFAO) examined two of them in detail. One groups the daily press coverage of supervised banks by theme, with TF-IDF and k-means clustering. Supervisors receive it as a daily early-warning report. The other uses elastic-net regression on historical supervisory data to estimate risk-weighted assets for small banks under simplified reporting. Its estimates feed into FINMA's risk assessment of small banks. In a report dated 14 October 2025 and published on 7 January 2026, the SFAO found that such AI methods can support and relieve specific supervisory tasks. It found that the systems already help in practice, for example in preparing data and analyses. It also found that FINMA has no structured procedure to measure the effect or cost-effectiveness of its AI systems. 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By April 2025 the lab had ten AI systems in production. The Swiss Federal Audit Office (SFAO) examined two of them in detail. One groups the daily press coverage of supervised banks by theme, with TF-IDF and k-means clustering. Supervisors receive it as a daily early-warning report. The other uses elastic-net regression on historical supervisory data to estimate risk-weighted assets for small banks under simplified reporting. Its estimates feed into FINMA's risk assessment of small banks. In a report dated 14 October 2025 and published on 7 January 2026, the SFAO found that such AI methods can support and relieve specific supervisory tasks. It found that the systems already help in practice, for example in preparing data and analyses. It also found that FINMA has no structured procedure to measure the effect or cost-effectiveness of its AI systems. Project leads rated seven of 12 production systems as having little influence on supervision and four as not relevant.","replication":{"produced_by":["The system for press coverage turned press texts into TF-IDF vectors, reduced them with principal component analysis and grouped them with k-means clustering.","For small banks, elastic-net regression on historical supervisory data and on figures from larger institutions produced estimates of risk-weighted assets."],"must_hold":["Supervisors use the press report only as a supplementary early-warning indicator.","Results may be less stable or reliable when data are atypical."],"echoes":[]}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["account","replication"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"}},"summary":{"total":91,"addressed":91,"known":27,"reviewed":2,"reviewed_complete":2,"reviewed_partial":0,"record_mapped":25,"review_not_assessed":64,"not_assessed":0,"complete":false,"by_state":{"value_present":27,"not_reported":0,"unresolved":64,"not_assessed":0,"not_applicable":0,"withheld":0,"source_unavailable":0}}},"presentation_version":"fa434da68c8186c167003ea51234b35c5a61f45a62b48b83a5256ed526a3f2dd"}